Guide

JOLTS explained

Nonfarm payrolls tell you how many jobs were added last month. The unemployment rate tells you how many people are looking. Neither answers the question hiring managers and Fed officials care about most: how much unfilled demand for workers remains? The Bureau of Labor Statistics Job Openings and Labor Turnover Survey (JOLTS) fills that gap. It tracks job openings, hires, quits, layoffs, and other separations across millions of U.S. establishments — giving investors a read on labor market tightness, worker confidence, and early layoff signals weeks after the headline jobs report. This guide covers what JOLTS measures, the key series and rates, the Beveridge curve linking openings to unemployment, how JOLTS fits the monthly macro calendar, a Harbor Manufacturing monthly labor read worked example, an indicator decision table, common pitfalls, and a practitioner checklist — alongside our nonfarm payrolls guide, unemployment rate explainer, and recession guide.

What JOLTS measures

JOLTS is a monthly establishment survey — employers report labor flows, not individuals. The sample covers roughly 21,000 nonfarm business and government establishments, drawn from the same universe as the payroll survey that produces nonfarm payrolls. Each month, respondents report counts for the last business day of the reference month across five core flows:

Job openings — positions that are open, available, and actively recruiting on the last day of the month.
Hires — all additions to payroll during the month, including rehires.
Total separations — all employees who left during the month, split into quits, layoffs/discharges, and other separations (retirements, deaths, transfers).
Quits — voluntary separations initiated by the employee.
Layoffs and discharges — involuntary separations initiated by the employer.

BLS publishes both levels (millions of jobs) and rates — each flow divided by total employment in the sample, expressed per 100 employees. Rates are more comparable across decades as the workforce grows. JOLTS data are seasonally adjusted and released on a lag: the report for March typically arrives in early May, roughly six weeks after the reference month and several weeks after the jobs Friday payroll release for the same month.

Why the Fed watches JOLTS closely

Chair Powell and FOMC members cite job openings and the quits rate in nearly every labor-market discussion. Openings measure demand for labor; unemployment measures supply. When openings outrun available workers, wages face upward pressure — a key input to monetary policy decisions. The quits rate proxies worker bargaining power: employees rarely quit without another offer or strong confidence in finding one. Layoffs rising while quits fall is an early cooling signature that payroll growth may slow two to three months later.

Key series: openings, hires, quits, and layoffs

Headline coverage focuses on job openings — the level that peaked above 12 million in 2022 and became the symbol of post-pandemic labor scarcity. But openings alone mislead: a posting can stay unfilled for months, and some employers leave listings open as a pipeline even when not urgently hiring. Pair openings with hires to see whether demand converts into actual employment.

The quits rate: voluntary turnover as confidence

The quits rate (quits divided by employment) averaged near 2.3% before 2020, spiked above 3% during the Great Resignation, and remains the cleanest real-time gauge of worker confidence. High quits imply workers trade up for better pay or conditions; low quits suggest fear of job loss or fewer outside options. Quits lead wage growth: when workers quit freely, employers must raise pay to retain and recruit. A falling quits rate with stable payrolls often precedes softer average hourly earnings in the NFP report.

Layoffs and discharges: the involuntary signal

The layoffs and discharges rate is typically the smallest separation category in expansions — often near 1% of employment — but spikes sharply in recessions. Unlike quits, layoffs are employer-driven and correlate with profit warnings, inventory gluts, and credit tightening. Watch the level change, not just the rate: a move from 1.0% to 1.4% sounds small but represents hundreds of thousands of additional job losses at the margin. Layoffs rising in construction and manufacturing before services is a classic late-cycle pattern.

Hires vs openings: the vacancy yield

Divide monthly hires by job openings to get an informal vacancy yield — how efficiently the market fills posted demand. A low yield (many openings, few hires) suggests skill mismatches, geographic friction, or employers fishing for candidates at below-market wages. A high yield means openings convert quickly — either strong matching or employers pulling postings as conditions soften. Neither extreme is automatically good or bad; context from quits and payrolls matters.

The Beveridge curve: openings vs unemployment

Plot job openings (or the openings rate) against the unemployment rate month by month and you get the Beveridge curve — a downward-sloping relationship in normal times: more vacancies when fewer people are unemployed, and vice versa. The curve summarizes labor market efficiency. During the pandemic recovery, the curve shifted outward: unemployment fell while openings stayed elevated, implying a structural mismatch — early retirements, childcare constraints, sector rotation, and geographic immobility.

If the curve shifts back inward (same unemployment with fewer openings), labor demand is normalizing without necessarily requiring higher unemployment — a soft-landing narrative. If unemployment rises while openings stay high, the curve moves along its slope — cyclical cooling. If both openings and unemployment rise together, something unusual is happening (measurement issues, participation changes, or sectoral shocks). Investors use the Beveridge curve to judge whether wage pressure can ease without a spike in joblessness.

Openings-to-unemployed ratio

A popular shorthand divides total job openings by total unemployed persons (from the household survey). Ratios above 1.0 mean more advertised vacancies than officially unemployed job seekers — a tight market. The ratio peaked near 2.0 in 2022 and falling toward 1.0 signals rebalancing. This ratio mixes establishment and household data, so methodological differences create noise; treat it as directional, not precise.

Sector and establishment detail

JOLTS publishes industry breakdowns for openings, hires, and separations. Sector patterns reveal rotation beneath national aggregates:

Professional and business services — large openings share; quits often lead national turns.
Healthcare and social assistance — structural demand; openings stay elevated even when cyclical sectors cool.
Leisure and hospitality — high turnover, low wages; quits rate swings amplify national averages.
Manufacturing — layoffs lead cyclical downturns; pair with industrial production and PMI employment sub-indexes.
Construction — openings track housing starts with a lag; layoffs rise when mortgage rates bite.
Retail trade and transportation — seasonal hiring spikes distort month-to-month changes; use three-month averages.
Government — slower quits, lower layoffs; less cyclical but budget cuts show up in layoffs first.

BLS also publishes size-class tables (small vs large establishments). Large firms post more openings but small firms drive hire rates in expansions. Regional data are limited in JOLTS; supplement with state unemployment claims and regional Fed surveys.

JOLTS in the monthly macro calendar

JOLTS arrives mid-month, after jobs Friday and often after CPI. By release day, markets may already have priced two newer payroll months. That does not make JOLTS stale — it confirms or contradicts the trend payrolls implied. Map the sequence using the economic calendar:

Weekly initial jobless claims — earliest layoff pulse; four-week average trends matter.
First Friday: NFP + unemployment rate — net job change and household unemployment.
Same week or next: ISM PMI employment sub-indexes — hiring sentiment diffusion.
Mid-month: JOLTS — openings, quits, layoffs for the payroll reference month.
Following weeks: CPI, retail sales, GDP revisions — demand context for whether labor cooling is demand- or supply-driven.

A classic divergence: payrolls beat consensus while JOLTS openings fall and quits decline — hiring happened, but forward demand for workers is easing. The next two payroll reports often soften. Conversely, weak NFP with rising openings may reflect supply constraints or survey noise, not collapsing demand.

Worked example: Harbor Manufacturing monthly labor read

Harbor Manufacturing — a fictional industrial equipment maker in our recurring macro examples — publishes an internal labor market note when JOLTS drops. Suppose the BLS releases March data in early May: job openings 8.5 million (down 350k from February, lowest since 2021), hires rate 3.6%, quits rate 2.2% (down 0.2pp), layoffs rate 1.1% (up 0.1pp). Openings fell most in professional services and retail; manufacturing openings flat but layoffs ticked up. The unemployment rate for March was 4.1% (from the earlier jobs report).

Harbor's workforce planning team writes:

Openings down, quits down — labor market rebalancing; workers less willing to leave; wage pressure should moderate in coming AHE prints.
Layoffs rate rising from a low base — not recessionary yet, but watch manufacturing layoffs against internal order backlog (which softened in Q1).
Openings-to-unemployed near 1.3 — still tighter than 2019, but far from 2022 extremes; recruiting difficulty easing for skilled machinists.
Hires rate stable — Harbor still filled open roles in March; the issue is fewer new reqs, not inability to hire.
Policy read — supports one fewer 2026 Fed hike priced; Harbor delays two planned production-line expansions but does not initiate layoffs; freezes one shift of overtime instead.

The lesson: JOLTS translates payroll headlines into forward hiring intent. Falling openings with rising layoffs at the margin beats a single NFP surprise for workforce planning.

Indicator decision table

Pattern	What it suggests	Typical market read
Rising openings, rising quits, flat layoffs	Tight labor market, worker confidence	Hawkish Fed bias; wage inflation risk; cyclical equities supported
Falling openings, falling quits, flat layoffs	Soft landing rebalancing	Dovish repricing without recession panic; bonds rally moderately
Falling openings, rising layoffs, falling quits	Demand cooling turning into job loss	Recession risk premium; duration bid; cyclicals underperform
Stable openings, falling hires	Matching friction or selective hiring freeze	Mixed; sector rotation more than macro panic
Rising layoffs in construction + manufacturing	Cyclical downturn in rate-sensitive sectors	Watch housing and PMI; Fed cut expectations rise
High openings, rising unemployment (outward Beveridge shift)	Skill/sector mismatch persists	Sticky wage pressure in shortage niches despite higher headline unemployment

Common pitfalls

Treating openings as exact job counts — postings can be duplicate, stale, or aspirational; hires are the realized demand.
Ignoring the release lag — JOLTS describes a month markets have largely moved past; use it for trend confirmation, not day-trading.
Overreacting to one month — seasonal adjustment errors and survey noise move openings hundreds of thousands; use three-month averages.
Mixing household and establishment concepts — the openings-to-unemployed ratio crosses surveys; understand the blend.
Equating quits with happiness — high quits in low-wage sectors often reflect churn, not career upgrades; read sector tables.
Missing government shutdown gaps — BLS delays or skips releases during funding lapses; series have level breaks after long pauses.
Forgetting revisions — JOLTS revises prior months; opening level shifts can rewrite the Beveridge curve picture.

Production checklist

Track openings, quits rate, and layoffs rate on the same chart with three-month moving averages.
Plot your Beveridge curve scatter (openings rate vs U-3) for the last five years to spot shifts vs slides.
Compare JOLTS reference month to the payroll month you already analyzed — note what changed in the narrative.
Read sector tables for your industry exposure before reacting to the national headline.
Pair JOLTS layoffs trend with initial jobless claims four-week average for confirmation.
Log the openings-to-unemployed ratio monthly; set alert thresholds for your macro model.
Cross-reference with PMI employment and GDP consumption for demand context.

Key takeaways

JOLTS measures labor flows — openings, hires, quits, and layoffs — not just net job change.
The quits rate signals worker confidence and leads wage pressure; layoffs rate signals employer-driven cuts.
The Beveridge curve links vacancies to unemployment; outward shifts imply mismatch, inward shifts imply normalization.
JOLTS lags payrolls by weeks but confirms whether hiring demand is strengthening or fading.
Sector detail matters: manufacturing layoffs and services quits tell different cyclical stories.